Co-infection Dynamics Research Articles

Mathematical modeling and analysis of leptospirosis–COVID-19 co-infection with real data

In this paper, we present a mathematical model to analyze the dynamics of leptospirosis and COVID-19 co-infection. The model used actual data, and estimation of the parameters via the MLE method is performed, which includes the rates of disease transmission, progression of the disease, disease-related death, and recovery rates for each disease and their co-infection. Key parameters: β1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta _1$$\\end{document}, β2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta _2$$\\end{document}, ϕ1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\phi _1$$\\end{document}, ϕ2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\phi _2$$\\end{document}, and μc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu _c$$\\end{document} are used to characterize the dynamics of the co-infection burden of leptospirosis and COVID-19. The results reveal a notable contrast in transmission dynamics and clinical outcomes between the two diseases, with leptospirosis demonstrating a higher transmission rate and increased morbidity. Co-infections showed more severe clinical outcomes, with higher mortality and delayed recovery than single infections. These findings highlight the importance of targeted public health strategies for managing co-infected populations.

Modeling optimal control strategies for HIV and gonorrhea co-infection: incorporating screening along with treatment

Abstract Human immunodeficiency virus (HIV) and gonorrhea are significant infectious diseases that pose considerable public health challenges worldwide. In this study, a control-induced model is developed to explore the dynamics of HIV and gonorrhea co-infection in the presence of treatment, incorporating screening strategies as control variables. We establish qualitative behavior, such as nonnegativity and boundedness of the solutions, and compute the basic reproduction number by utilizing the next generation matrix method. Subsequently, the stability of the disease-free equilibrium is analyzed, and then sensitivity analysis is undertaken to pinpoint the most critical parameters. Furthermore, an optimal control problem is formulated to diminish the total count of infected individuals and associated costs. The existence of an optimal control is shown, and Pontryagin’s principle is employed to derive the necessary conditions for an optimality system. Additionally, numerical simulations reveal that without control measures, the model predicts a continual rise in the number of infections. However, the graphical results demonstrate that the simultaneous implementation of screening for both HIV and gonorrhea as control measures significantly reduces single infections as well as co-infections. These insights are vital for researchers and policymakers to develop effective intervention strategies for eradicating co-infections of HIV and gonorrhea.

A mathematical model of Cholera–Typhoid coinfection dynamics with dual-seasonally driven contact rates

Cholera and Typhoid Fever place a huge burden on public health systems of predominantly Asian and African countries. Poor sanitation and suboptimal treatment of these infections have been the primary causes of the resurgence of these infections in recent years. A mathematical model, consisting of a dynamical system, is used to model the progression of cholera, typhoid and co-infection cases over time. The seasonality of the infections is modelled using trigonometric functions. The findings show that during peak transmission, the severity of cholera and typhoid is determined by the presence or absence of a peak in coinfection cases.

A fractional-order model of COVID-19 and Malaria co-infection

This paper explores the co-infection dynamics of coronavirus disease 2019 (COVID-19) and Malaria using Caputo-type fractional derivative to further understand the disease interactions and implement effective control strategies. We demonstrate the positivity and boundedness of the solution through Laplace transform techniques and establish the existence and uniqueness of the solution, showcasing model stability using fractional-order stability theory. Simulation experiments across varying fractional orders and disease classes offer insights into the co-infection dynamics. This is a new model and the findings underscore the potential impact of control measures on mitigating co-infection under endemic conditions. We conclude that infection with malaria does not guarantee immunity to COVID-19 and infection with COVID-19 as well does not guarantee immunity to malaria.

A mathematical model of Cholera–Typhoid coinfection dynamics with a hygiene-driven contact rate

Waterborne infections such as Cholera and Typhoid remain a huge burden on the public health systems of poor countries in Africa and Asia. The highest disease burden is concentrated in sub-Saharan Africa. In most regions, the recent spike in cases of both infections is attributed to dilapidated infrastructure and poor hygiene. This paper examines the role of poor hygiene in the surge of both infections. We use a system of non-linear ordinary differential equations to model the movement of people between the different classes of infections, and we use a sigmoidal function to model the different levels of hygiene in a community. The findings demonstrate that managing hygiene, even if limited to the direct transmission route, can significantly reduce the prevalence of both infections. This paper presents some of the public health implications of these findings.

Discovering Variability in Population of T-Lymphocyte Subsets Present in Peripheral Blood of Patients Co-Infected by HIV and HBV Through Laboratory Medicine

An alarming number of 296 million individuals in Egypt have recently been diagnosed as HBV positive; because these two viruses share similar routes of transmission, about 10% of this population is also thought to be HIV positive. It is widely acknowledged that coinfection with HIV and HBV has a significant negative effect on the immune system and accelerates the loss of T-lymphocyte subpopulations, which are essential for immunological defense. This enlightening study, carried out in Cairo, Egypt, explores the complicated dynamics of T-cell subsets and carefully looks at the immunological effects and frequency of coinfection between HIV and HBV. Naturally, of the 35 patients in the cohort under examination, an impressive 8.4% had coinfections with HBV and HIV. Systematic immunophenotyping of several T-cell subsets, such as CD4+, CD8+, CD45RO, CD16+56, and CD45RA, was used in the study, and the results showed clear differences between coinfected and mono-infected peopleUsing trustworthy methods like microfluid inertial separation and flow cytometry has given researchers significant insights into the complex immunological circumstances connected to HIV/HBV coinfection. Interestingly, a significant decrease in CD4+ cells—a crucial marker of HIV progression—was observed in over 50% of the coinfected patients, suggesting an accelerated course of the illness in these individuals. Moreover, the study establishes the foundation for particular treatment strategies and adds to our scientific understanding coinfection dynamics. These therapies, based on the study’s detailed findings, can potentially improve patient outcomes despite this difficult coinfection setting. To manage the difficulties of HIV/HBV coinfection, the research emphasizes the importance of ongoing attention and the incorporation of cutting-edge diagnostic techniques, eventually advancing public health activities.

Stochastic modeling and analysis of Hepatitis and Tuberculosis co-infection dynamics

Abstract Several mathematical models have been developed to investigate the dynamics of Tuberculosis (TB) and Hepatitis B virus (HBV). Numerous current models for TB, HBV, and their co-dynamics fall short in capturing the important and practical aspect of unpredictability. It is crucial to take into account a stochastic co-infection HBV–TB epidemic model since different random elements have a substantial impact on the overall dynamics of these diseases. We provide a novel stochastic co-model for TB and HBV in this study, and we establish criteria on the uniqueness and existence of a non-negative global solution. We also looked at the persistence of the infections as long its dynamics are governable by the proposed model. To verify the theoretical conclusions, numerical simulations are presented keeping in view the associated analytical results. The infections are found to finally die out and go extinct with certainty when Lévy intensities surpass the specified thresholds and the related stochastic thresholds fall below unity. The findings also demonstrate the impact of noise on the decline in the co-circulation of HBV and TB in a given population. Our results provide insights into effective intervention strategies, ultimately aiming to improve the management and control of TB and HBV co-infections.

Dynamical and optimal control analysis of lymphatic filariasis and buruli ulcer co-infection

This study delves into the dynamics of lymphatic filariasis and buruli ulcer coinfection, two overlooked yet impactful tropical diseases. With lymphatic filariasis, commonly referred to as elephantiasis, and buruli ulcer, a chronic affliction caused by mycobacterium ulcerans, both posing significant health challenges, understanding their interaction is crucial. Utilizing a mathematical model, this research aims to analyze the dynamics of this coinfection, elucidating its complexities. The study establishes the local asymptotic stability of the disease-free equilibrium and calculates the basic reproduction number using the next generation matrix. It uncovers transcritical and backward bifurcation phenomena within the model. Additionally, the integration of time-dependent controls enables the exploration of optimal disease management strategies. Numerical simulations highlight the efficacy of employing a comprehensive approach, utilizing all available controls simultaneously, as the most effective strategy for disease control. These findings underscore the importance of integrated interventions in combating lymphatic filariasis and buruli ulcer coinfection, offering valuable insights for public health policymakers and practitioners.

Co-infection dynamics of B. afzelii and TBEV in C3H mice: insights and implications for future research.

Ticks are important vectors of disease, particularly in the context of One Health, where tick-borne diseases (TBDs) are increasingly prevalent worldwide. TBDs often involve co-infections, where multiple pathogens co-exist in a single host. Patients with chronic Lyme disease often have co-infections with other bacteria or parasites. This study aimed to create a co-infection model with Borrelia afzelii and tick-borne encephalitis virus (TBEV) in C3H mice and to evaluate symptoms, mortality, and pathogen level compared to single infections. Successful co-infection of C3H mice with B. afzelii and TBEV was achieved. Outcomes varied, depending on the timing of infection. When TBEV infection followed B. afzelii infection by 9 days, TBEV symptoms worsened and virus levels increased. Conversely, mice infected 21 days apart with TBEV showed milder symptoms and lower mortality. Simultaneous infection resulted in mild symptoms and no deaths. However, our model did not effectively infect ticks with TBEV, possibly due to suboptimal dosing, highlighting the challenges of replicating natural conditions. Understanding the consequences of co-infection is crucial, given the increasing prevalence of TBD. Co-infected individuals may experience exacerbated symptoms, highlighting the need for a comprehensive understanding through refined animal models. This study advances knowledge of TBD and highlights the importance of exploring co-infection dynamics in host-pathogen interactions.

Mixed viral infections in vegetable crops: biochemical and molecular aspects

Mixed viral infections refer to the coinfection of two or more viruses in the plant, which regularly lead to exacerbated symptoms on leaves and fruits. The dynamics of coinfections may follow either a synergistic, antagonistic, or neutral interaction that impacts the severity of the symptoms and infection. Mixed viral infections occur due to the convergence of fundamental characteristics reviewed in this manuscript. The virus‒host plant interrelationship influences the establishment and spread patterns of mixed viral infections. Attention should be drawn to potential changes in the dynamics of transmission and prevalence of plant viral diseases due to the effect of anthropogenic and natural alterations to complex agroecological systems or their components, including hosts, reservoirs, vectors, ecological niches, and the emergence of new virus strains.

Order of arrival and nutrient supply alter outcomes of co-infection with two fungal pathogens.

A pathogen arriving on a host typically encounters a diverse community of microbes that can shape priority effects, other within-host interactions and infection outcomes. In plants, environmental nutrients can drive trade-offs between host growth and defence and can mediate interactions between co-infecting pathogens. Nutrients may thus alter the outcome of pathogen priority effects for the host, but this possibility has received little experimental investigation. To disentangle the relationship between nutrient availability and co-infection dynamics, we factorially manipulated the nutrient availability and order of arrival of two foliar fungal pathogens (Rhizoctonia solani and Colletotrichum cereale) on the grass tall fescue (Lolium arundinaceum) and tracked disease outcomes. Nutrient addition did not influence infection rates, infection severity or plant biomass. Colletotrichum cereale facilitated R. solani, increasing its infection rate regardless of their order of inoculation. Additionally, simultaneous and C. cereale-first inoculations decreased plant growth and-in plants that did not receive nutrient addition-increased leaf nitrogen concentrations compared to uninoculated plants. These effects were partially, but not completely, explained by the duration and severity of pathogen infections. This study highlights the importance of understanding the intricate associations between the order of pathogen arrival, host nutrient availability and host defence to better predict infection outcomes.

Link between bacterial communities and contrasted loads in ectoparasitic monogeneans from the external mucus of two wild sparid species (Teleostei)

BackgroundWhile teleost fishes represent two thirds of marine vertebrates, the role of their external microbiota in relationship with their environment remains poorly studied, especially in wild populations. Hence, the interaction of their microbiota with ectoparasites is largely unknown. Microbiota can act as a protective barrier against pathogens, and/or be involved in host recognition by parasites. Thus, host-parasite associations should now be considered as a tripartite interplay where the microbiota shapes the host phenotype and its relation to parasites. Monogeneans (Platyhelminthes) are direct life cycle ectoparasites commonly found on teleost skin and gills. The role of bacterial communities within skin and gill mucus which either pre-exist monogeneans infestation or follow it remain unclear. This is investigated in this study using the association between Sparidae (Teleostei) and their specific monogenean ectoparasites of the Lamellodiscus genus. We are exploring specificity mechanisms through the characterization of the external mucus microbiota of two wild sparid species using 16s rRNA amplicon sequencing. We investigated how these bacterial communities are related to constrated Lamellodiscus monogeneans parasitic load.ResultsOur results revealed that the increase in Lamellodiscus load is linked to an increase in bacterial diversity in the skin mucus of D. annularis specimens. The date of capture of D. annularis individuals appears to influence the Lamellodiscus load. Correlations between the abundance of bacterial taxa and Lamellodiscus load were found in gill mucus of both species. Abundance of Flavobacteriaceae family was strongly correlated with the Lamellodiscus load in gill mucus of both species, as well as the potentially pathogenic bacterial genus Tenacibaculum in D. annularis gill mucus. Negative correlations were observed between Lamellodiscus load and the abundance in Vibrionaceae in gill mucus of D. annularis, and the abundance in Fusobacteria in gill mucus of P. acarne specimens, suggesting potential applications of these bacteria in mitigating parasitic infections in fish.ConclusionsOur findings highlight the dynamic nature of fish microbiota, in particular in relation with monogeneans infestations in two wild sparid species. More generally, this study emphasizes the links between hosts, bacterial communities and parasites, spanning from the dynamics of co-infection to the potential protective role of the host’s microbiota.

A Mathematical Model for the Co-infection Dynamics of Pneumocystis Pneumonia and HIV/AIDS with Treatment

The control of opportunistic infections among HIV infected individuals should be one of the major public health concerns in reducing mortality rate of individuals living with HIV/AIDS. In this study a deterministic co-infection mathematical model is developed to provide a quantification of treatment at each contagious stage against Pneumocystis Pneumonia (PCP) among HIV infected individuals on ART. The goal is to minimize the co-infection burden by putting the curable PCP under control. The disease-free equilibria for the HIV/AIDS sub-model, PCP sub-model and the co-infection model are shown to be locally asymptotically stable when their associated disease threshold parameter is less than a unity. By use of suitable Lyapunov functions, the endemic equilibria corresponding to HIV/AIDS and PCP sub-models are globally asymptotically stable whenever the HIV/AIDS related basic reproduction number <I>R</I><sub>0<I>H</I></sub> and the PCP related reproduction number <I>R</I><sub>0<I>P</I></sub> are respectively greater than a unity. The sensitivity analysis results implicate that the effective contact rates are the main mechanisms fueling the proliferation of the two diseases and on the other hand treatment efforts play an important role in reducing the incidence. The model numerical results reveal that PCP carriers have a considerable contribution in the transmission dynamics of PCP. Furthermore, treatment of PCP at all contagious phases significantly reduces the burden with HIV/AIDS and PCP co-infection.

Correlates of Co-Infection with Coccidiosis and Avian Malaria in House Finches (Haemorhous mexicanus).

Pathogens have traditionally been studied in isolation within host systems; yet in natural settings they frequently coexist. This raises questions about the dynamics of co-infections and how host life-history traits might predict co-infection versus single infection. To address these questions, we investigated the presence of two parasites, a gut parasite (Isospora coccidians) and a blood parasite (Plasmodium spp.), in House Finches (Haemorhous mexicanus), a common passerine bird in North America. We then correlated these parasitic infections with various health and condition metrics, including hematological parameters, plasma carotenoids, lipid-soluble vitamins, blood glucose concentration, body condition, and prior disease history. Our study, based on 48 birds captured in Tempe, Arizona, US, in October 2021, revealed that co-infected birds exhibited elevated circulating lutein levels and a higher heterophil:lymphocyte ratio (H/L ratio) compared to those solely infected with coccidia Isospora spp. This suggests that co-infected birds experience heightened stress and may use lutein to bolster immunity against both pathogens, and that there are potentially toxic effects of lutein in co-infected birds compared to those infected solely with coccidia Isospora sp. Our findings underscore the synergistic impact of coparasitism, emphasizing the need for more co-infection studies to enhance our understanding of disease dynamics in nature, as well as its implications for wildlife health and conservation efforts.

Modeling the dynamics of co-infection between COVID-19 and tuberculosis with quarantine strategies: A mathematical approach

Modeling the dynamics of co-infection between COVID-19 and tuberculosis with quarantine strategies: A mathematical approach

Cost-effectiveness analysis of optimal control strategies on the transmission dynamics of HIV and Varicella-Zoster co-infection

HIV and Varicella-Zoster co-infection has been threatens the lives and livelihood of millions of individuals all over the world. In various nations of the world the co-infection disease is presently a major health problem. Although, various researchers carried out studies related with HIV and Zoster single infections, no one has carried out a study on the co-infection disease. Therefore, investigating the HIV and Varicella-Zoster co-infection transmission dynamics using mathematical modeling approach is relatively necessary. The main objective of this study is to investigate the cost-effective analysis of the proposed optimal control strategies on the transmission dynamics of HIV and Varicella-Zoster co-infection in the community using compartmental modeling approach. Qualitatively, we have computed the model equilibrium points and analyze their local stabilities using Routh-Hurwitz stability criteria, the effective reproduction numbers by using the next generator matrix operator method, we re-formulated the optimal control problem of the complete co-infection model by implementing five time dependent optimal control strategies, analyzed the optimal control problem by applying the Pontryagin's Maximum/Minimum principle. Sensitivity analysis and numerical simulations have been carried out using the forward sensitivity index formula and the fourth order Runge-Kutta numerical methods respectively and verified the analytic results. Finally, we have performed the cost effective analysis for the proposed controlling strategies and from the result we have observed that implementing strategy four (treatment of Varicella-Zoster infected individuals to increase their recovery rate and recovery period) is the most cost effective-strategy as compared with other alternatives.

Modeling and investigating malaria P. Falciparum and P. Vivax infections: Application to Djibouti data

Malaria is an infectious and communicable disease, caused by one or more species of Plasmodium parasites. There are five species of parasites responsible for malaria in humans, of which two, Plasmodium Falciparum and Plasmodium Vivax, are the most dangerous. In Djibouti, the two species of Plasmodium are present in different proportions in the infected population: 77% of P. Falciparum and 33% of P. Vivax. In this study we present a new mathematical model describing the temporal dynamics of Plasmodium Falciparum and Plasmodium Vivax co-infection. We focus briefly on the well posedness of this model and on the calculation of the basic reproductive numbers for the infections with each Plasmodium species that help us understand the long-term dynamics of this model (i.e., existence and stability of various eqiuilibria). Then we use computational approaches to: (a) identify model parameters using real data on malaria infections in Djibouti; (b) illustrate the influence of different estimated parameters on the basic reproduction numbers; (c) perform global sensitivity and uncertainty analysis for the impact of various model parameters on the transient dynamics of infectious mosquitoes and infected humans, for infections with each of the Plasmodium species. The originality of this research stems from employing the FAST method and the LHS method to identify the key factors influencing the progression of the disease within the population of Djibouti. In addition, sensitivity analysis identified the most influential parameter for Falciparium and Vivax reproduction rates. Finally, the uncertainty analysis enabled us to understand the variability of certain parameters on the infected compartments.

A new co-infection model for HBV and HIV with vaccination and asymptomatic transmission using actual data from Taiwan

The co-infection of Human Immunodeficiency Virus (HIV) and Hepatitis B virus (HBV) poses a major threat to public health due to their combined negative impacts on health and increased risk of complications. A novel fractional mathematical model of the dynamics of co-infection between HBV and HIV for Taiwan is presented in this paper. Detailed analyses are conducted on the possible impact of HBV vaccination on the dynamics of HBV and HIV co-infection. The next-generation matrix technique is used to calculate the fundamental reproduction number R 0 = max{R 1, R 2}, where R 1 and R 2 are the reproduction numbers for HBV and HIV, respectively. The disease-free and endemic equilibria of the co-infection model are calculated. An extensive investigation is carried out to determine the local and global stability of the disease-free equilibrium point through Rough Hurtwiz criteria and the construction of Lyapunov function, respectively. We demonstrate that when R 1 < 1 < R 2, HBV infection is eradicated, but HIV remains prevalent. If R 2 < 1 < R 1, the opposite outcome occurs. The real data from 2000-2023 for Taiwan is used to fit the model. The fitting results show how effectively our model handles the data. In addition, numerical simulations are run for different scenarios to observe how the vaccine and fractional parameters changed the model state variables, as well as how the solutions behaved and how quickly they reached the model’s equilibrium points. According to the model’s numerical analysis, greater vaccination efforts against HBV have a positive effect on the propagation of co-infection.

Mathematical Modelling of Tuberculosis and Hepatitis C Coinfection Dynamics with No Intervention

In this study, a deterministic tuberculosis (TB)-hepatitis C (HCV) coinfection mathematical model with no intervention is analysed purposely to examine the dynamics of TB-HCV coinfection so as to find conditions for reducing the transmission of both TB and HCV. A unique solution to the model exists; it is positive and is bounded. The analytical and numerical analysis show that for basic reproduction number, R0=maxRT,RH&lt;1, the TB and HCV disease-free equilibrium points are stable. Further analysis shows that when the TB-HCV coinfection basic reproduction number is greater than 1, the endemic equilibrium point is stable. Sensitivity analysis reveals that interventions to reduce TB or HCV infection need to aim and concentrate on minimizing the numbers of the effective contact rate with TB- or HCV-infected humans and the rate of progress from latent TB or acute HCV to infectious TB or chronic HCV stage. Numerical simulations reveal that over time, the number of TB latent humans, acute HCV humans, and the number of dually infected humans have a linear relationship with the effective contact and the progression rates for both TB- and HCV-infected humans. We recommend that health education campaigns to communities aimed at reducing the transmission rates of TB and HCV be conducted. These could include screening and isolation, wearing of face masks for TB cases and screening, sterilization of surgical instruments, and use of condoms for HCV-infected humans.

Analyzing co-infection dynamics: A mathematical approach using fractional order modeling and Laplace-Adomian decomposition

The co-infection of HIV and COVID-19 is a pressing health concern, carrying substantial potential consequences. This study focuses on the vital task of comprehending the dynamics of HIV-COVID-19 co-infection, a fundamental step in formulating efficacious control strategies and optimizing healthcare approaches. Here, we introduce an innovative mathematical model grounded in Caputo fractional order differential equations, specifically designed to encapsulate the intricate dynamics of co-infection. This model encompasses multiple critical facets: the transmission dynamics of both HIV and COVID-19, the host’s immune responses, and the influence of treatment interventions. Our approach embraces the complexity of these factors to offer an exhaustive portrayal of co-infection dynamics. To tackle the fractional order model, we employ the Laplace-Adomian decomposition method, a potent mathematical tool for approximating solutions in fractional order differential equations. Utilizing this technique, we simulate the intricate interactions between these variables, yielding profound insights into the propagation of co-infection. Notably, we identify pivotal contributors to its advancement. In addition, we conduct a meticulous analysis of the convergence properties inherent in the series solutions acquired through the Laplace-Adomian decomposition method. This examination assures the reliability and accuracy of our mathematical methodology in approximating solutions. Our findings hold significant implications for the formulation of effective control strategies. Policymakers, healthcare professionals, and public health authorities will benefit from this research as they endeavor to curtail the proliferation and impact of HIV-COVID-19 co-infection.